The conventional data envelopment analysis (DEA) measures the relative efficiencies of a set of decision making units (DMUs) with exact value of inputs and outputs. For imprecise data, i.e., mixtures of interval data and ordinal data, some methods have been developed to calculate the interval of the efficiency scores. This paper constructs a procedure to measure the efficiencies of DMUs with mi...

in this paper, we show that inverse data envelopment analysis (dea) models can be used to estimate output with fuzzy data for a decision making unit (dmu) when some or all inputs are increased and deficiency level of the unit remains unchanged.

this paper gives a new application of dea to evaluate the scheduling solutions of parallel processing. it evaluates the scheduling solutions of parallel processing using the non-convex dea model, fdh model. by introducing each solution of parallel processing scheduling as a dmu with some relevant inputs and outputs this paper shows that how the most efficient schedule(s) can be identified.

evaluation of corporate performance has been one of the main issues in managing decision making. nowadays, evaluation of the suppliers is a completely strategic process because organizations rarely change their suppliers. thesuppliers also do their best to remain stable in the loop of supply chain. hence, it is important to evaluate the suppliers and not something to be done once at a time. it ...

data envelopment analysis (dea) has been widely studied in the literature since its inception with charnes, cooper and rhodes work in 1978. the methodology behind the classical dea method is to determine how much improvements in the outputs (inputs) dimensions is necessary in order to render them efficient. one of the underlying assumptions of this methodology is that the units consume and prod...

It is well known that Data Envelopment Analysis (DEA) is a relative efficiency measurement tool, which uses optimization techniques to automatically calculate the weights assigned to the crisp deterministic multiple inputs and outputs of a set of the Decision Making Units (DMUs) being assessed. However, crisp deterministic data requirement delimits an application to the real world problems wher...

We developed an alternative approach for measuring information and communication technology (ICT), applying Data Envelopment Analysis (DEA) using data from the International Telecommunications Union as a sample of 183 economies. We compared the ICT-Opportunity Index (ICT-OI) with our DEAOpportunity Index (DEA-OI) and found a high correlation between the two. Our findings suggest that both indic...

Data envelopment analysis is computationally intensive. The standard approach requires the solution of as many LPs as there are points in the data domain, each with as many columns. This number is frequently in the thousands and multi-period DEA amplifies the problem. Enhancements that reduce the size of the LPs are possible and a new scheme consisting of partitioning the domain offers more tim...

Chiou et al. (2010) (A joint measurement of efficiency and effectiveness for non-storable commodities: integrated data envelopment analysis approache s. European Journal of Operationa l Research 201, 477– 489) propose an integrated data envelopment analysis model in measuring decision making units (DMUs) that have a two-stage internal netwo rk structure with multiple inputs, outputs, and consum...